SUSTAINABILITY OF ORGANIC DAIRYING IN CANADA
Bibliographic record
Abstract
The distinctive production characteristics and economic performance of organic dairy farms in central Canada has been documented, but the sustainability of these systems with respect to farm nutrient flows is less well understood. We have assessed farm management, livestock productivity, and nutrient status of fifteen long term (>10y) certified organic dairy farms in Ontario, Canada. Farm size, herd size and herd productivity averaged 110 ha, 52 cows and 8207 kg milk cow yr-1, respectively. Cropping composition differed little between farms, with pasture and forage accounting for an average of 65% of the cropped landbase. Annual farm nutrient budgets (inputs-outputs) over two years (2003-2005) for N, P and K were 52, 1 and 11 kg ha-1 yr-1, respectively. The majority (13) of farms had positive K budgets with half of the farms recording negative annual P budgets. Nutrient budget results were supported by soil fertility data generated by sampling 80% of farm fields (n=225). Overall, these results contrast strongly with large nutrient surpluses reported for more intensive, confinement-based dairy farms throughout N. America, but suggest a challenge to remain sustainable over the longer term for the 50% of these farms adopting a broadly ‘self-sufficient’ approach, and importing little P (0 - 2.5 kg ha-1 yr-1) as feed and feed supplements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".